Multi-sensor Precipitation Estimator (MPE)

Jennifer H. MaxwellColorado Basin River Forecast Center

What Is MPE?

• MPE = multi-sensor precipitation estimator• “MPE’s focus is on areal estimations of

rainfall amounts based on both remotely sensed data (radar, and eventually satellite) and actual observations (rain gages).”

Original Purpose

• The purpose of RFC-wide MPE is to create hourly gridded precipitation estimates which can be used to produce MAPX time series for input into NWSRFS

• MPE is intended to replace the stage2/ stage3 processing at River Forecast Centers

History

• Stage III (still being used by several RFC’s)• Stand alone version of RFC_wide (now

called MPE) used at river forecast centers• HMAP_MPE as part of WHFS Hydroview

MPE Primary Inputs/Outputs

• The primary inputs to MPE are the griddedDPA products and precipitation gage data.

• MPE creates hourly, gridded, multi-sensor precipitation estimates on a 4 km HRAP grid.

MPE Capabilities

• Multi-radar mosaic according to the lowest available height above sea level

• Individual radar coverage maps determined by HDP/DPA climatology

• Mean field bias adjustment of raw radar estimates through multiple time scales

• Merging of rain gage and radar data

MPE Capabilities Cont.

• Local bias adjustment which varies from grid point to grid point

• Use and display of PRISM data• Manual quality control of gage and radar

data (GUI)• Display and use of satellite-derived

precipitation estimates (build OB1?)

Why Are We Using MPE?

• MPE creates a 1 hourly precipitation estimate that we can now feed into the model to support 1 hourly time segments

• Incorporates radar data• Can QC the data

1 Hourly Time Segment Areas

Radar Climatology

• Determination of “trusted” radar coverage– To compute radar-derived precipitation

climatologies we used:• Frequency of precipitation• Defined a threshold to be placed on the precipitation

estimates• Created different radar masks based on season and

latitude• Choose lowest available coverage

Summer Radar Masks

Fall/spring Radar Masks

Displays in MPE

• Gridded precipitation products• Other Gridded fields • Tables • Radar masks

Raw Radar (RMOSAIC)

Bias Corrected Radar (BMOSAIC)

Bias Table

Local Bias (LMOSAIC)

Bias Correction Factor (LOCBIAS)

Memory Span (LOCSPAN)

Gage Only

Multi-sensor (MMOSAIC)

XMRG (Saved Product)

Height of Radar Coverage

Prism Data

Gage Table

Single Radar Site

Forecaster Input

• Ability to edit the gridded data fields as well as the point gage observations

• Provides tools to edit gage values, bias values, Z-R relationship values, and then rerun estimation algorithms

• The user can add a pseudo gage to adjust the radar values

Forecaster Input

• There is also an edit precipitation capability which allows the user to draw a polygon around a region of interest. The user can then substitute any of the precipitation fields (RMOSAIC, BMOSAIC, MMOSAIC, LMOSAIC, SATELLITE) into the region outlined by the polygon.

• After a forecaster has finished analyzing and editing the precipitation data, the final analysis can be saved as an xmrg file for input into MAPX.

Problems in the West

• Limited “trusted” radar coverage• Some areas with no gage/radar values• Gage radius of influence• Radar bias (i.e. RIW problems)• Satellite estimates not available yet• Adding our own estimates?

Local Changes

• Increased radius of influence on gages• Changed precipitation amount for gage-

radar pairs (take fewer pairs to adjust radar bias)

• Modified radar coverage

Documentation

• http://www.nws.noaa.gov/oh/hrl/presentations/mpe_training_wkshp_0601/course_outline.htm

• http://www.nws.noaa.gov/oh/hod_whfs